Call:
lm(formula = valence ~ z_hppy, data = stand_ds)
Residuals:
Min 1Q Median 3Q Max
-0.55939 -0.20947 0.00818 0.17684 0.55637
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.526267 0.006890 76.38 <2e-16 ***
z_hppy 0.090781 0.007132 12.73 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.2357 on 1168 degrees of freedom
Multiple R-squared: 0.1218, Adjusted R-squared: 0.1211
F-statistic: 162 on 1 and 1168 DF, p-value: < 2.2e-16
To check this prediction we perform a moderation analysis. We keep the standardized version of the happiness scores because of the same reasons exposed in the simple linear regression.
Performing a moderation analysis implies entering the domains of the multiple linear regression (i.e. now there os more than one predictor). This means that the multicollinearity between predictors must be checked. To do so we look at the VIF values of the two predictors used, and there seems to be no multicollinearity at all.
X sophistication X:sophistication
1.004144 1.000172 1.004172
The model points at the interaction term being not significant and R2 = 0.1043. This points at our prediction not being met: the interaction is not significant and including this interaction term into the regression
Call:
lm(formula = Y ~ X + sophistication + X * sophistication)
Residuals:
Min 1Q Median 3Q Max
-0.56948 -0.20703 0.01238 0.17519 0.53605
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.262e-01 6.956e-03 75.650 <2e-16 ***
X 5.202e-02 4.413e-03 11.787 <2e-16 ***
sophistication 3.641e-05 3.944e-04 0.092 0.926
X:sophistication -2.765e-04 2.407e-04 -1.149 0.251
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.2379 on 1166 degrees of freedom
Multiple R-squared: 0.1066, Adjusted R-squared: 0.1043
F-statistic: 46.36 on 3 and 1166 DF, p-value: < 2.2e-16
Although the fit statistics already point at our prediction being not supported by the data, we can explore it visually. To do so we plot the valence distribution of songs at each level of happiness, for three different sophistication levels. If there was a moderation effect we would expect the direction of the relationship to change significantly in at least one of the three sophistication levels. Nevertheless, in all three plots, the relationship between valence and happiness seems identical.
To check this prediction we use the Levene’s test. In doing so we compare the happiness scores variance of the ‘low’,‘mid’ and ‘high’ sophistication group for each of the 15 songs. If the test shows a significant p-value, at least one of the groups has a different variance than the others. To see exactly what group has this different variance and visualize the data, we plot the happiness score distribution for each sophistication group using a boxplot. If our prediction was supported by the data, then the dark green box (i.e. variance of the highly sophisticated participants) would be systematically smaller than the lighter green boxes (i.e. variance of the ‘mid’ and ‘low’ participants). As a final note, Levene’s test’s p-values are corrected for multiplied testing using Bonferroni’s correction.
As we can see from the corrected Levene’s tests p-value, none of the songs groups have different variances. From visual inspection we can also see that the dark green box does not tend to be smaller than the other two.
It could be the case that our sample has a low sophistication in general. This would mean that our ‘high’ group still has a low sophistication in absolute terms, and thus we are not able to infer anything about highly sophisticated people and variance in happiness scores. To check this we plot the music sophistication distribution in our sample. We can see here nevertheless, that sophistication levels are sufficiently spread and we can consider our sample representative enough.
The demand for music has grown to become an important aspect of many peoples’ everyday life (Fuentes et al., 2019). Especially, the mode of music listening has shifted from only actively listening to music from time to time, to the soundtracking of daily activities. People accompany various activities with music, and it becomes an affective-practical resource. Several studies have focused on Music Emotion Recognition (MER) (Aljanaki et al. 2014). It focuses mostly on two dimensions: “valence (positive vs. negative) and arousal (quiet vs. energetic). However, the perfect MER model has not yet been found, as subjective and objective views on music often differ greatly (REF).
This study will try to understand the measurement of valence and whether subjective and objective valence differs as much in our sample. Additionally, many studies have shown that musical sophistication has an effect on the relationship between objective and subjective musical perception (REF). We will examine whether the level of expertise in music will impact musical perception in the context of valence, leading to the following research question:
To what extent does objective valence judgement predict subjective happiness ratings and to what extent is this relationship moderated by music sophistication?
The original data set contained 103 responses, but some had to be dropped. 21 participants did not finish the questionnaire and were thus removed from the data set. Furthermore, four participants took less than four minutes to complete the questionnaire. This was considered unreasonably low and so these responses were also removed from the data set. After this cleaning process, the data set contained 78 responses.
| id | name | valence |
|---|---|---|
| song1 | cold heart – pnau remix | 0.934 |
| song2 | industry baby (feat. jack harlow) | 0.892 |
| song3 | ibiza | 0.880 |
| song4 | amsterdam | 0.736 |
| song5 | le bled | 0.598 |
| song6 | bad habits | 0.537 |
| song7 | hard to say goodbye | 0.418 |
| song8 | where are you now | 0.262 |
| song9 | do it do it | 0.637 |
| song10 | moth to a flame (with the weeknd) | 0.109 |
| song11 | easy on me | 0.130 |
| song12 | thunder | 0.403 |
| song13 | ghost | 0.473 |
| song14 | heat waves | 0.531 |
| song15 | remember (and david guetta) | 0.354 |